A new generation of bike-sharing services is emerging in China. With this service, bikes can be unlocked and paid by using a smartphone and then picked up and left anywhere at users' convenience. The ...unprecedented development of dockless bike-sharing services results in considerable socioeconomic and environmental benefits but also creates new urban issues. One of the most severe issues is users’ inappropriate parking behaviour. To solve this problem, electric fence (or geo-fence) policy and technology have been introduced in China to guide users to park bikes in designated zones. In this paper, we first propose a methodological framework to support electric fence planning for dockless bike-sharing services. We then apply our framework in a case study of Shanghai using a big dataset of bike trips. Results show that when the number of planned electric fences is 7,500, our electric fence plan can cover 91.8% of total parking demand. In addition, our plan can ensure that at least 95.8% of all bikes can be docked at one of planned electric fences and can help efficiently and accurately determine suitable locations for setting up planned electric fences.
•We discuss electric fence (geo-fence) policy and technology used to regulate inappropriate parking behaviour.•We propose a methodological framework to support electric fence planning.•We apply our methods in a case study of Shanghai and present the results in six scenarios.•We adopt a big data approach to support our analysis.
Ships are the most important means of transportation for maintaining the marine economy in most countries. Coastal patrol is an important task of the state to prevent smuggling and other dangerous ...coastal activities. However, unfortunate accidents involving people on board ships and coast guards drowning in the sea occur from time to time. To save the lives of those who have fallen into the sea, most international searches are carried out by satellite searches, helicopter rescue, and the dispatch of boats. They are not only time-consuming but also inefficient. For this reason, we propose in this paper a real-time alarm, dynamic global positioning system (GPS) tracking, and monitoring system for man overboard (MOB). The system consists of four parts: wearable sensing aids, modular long-range access points (LoRa APs), physical electric fences, and a central control system, as well as three methods of detecting and protecting against MOB. These methods include real-time notification of MOB with wearable sensing aids, virtual electric fence monitoring based on the size of the ship, and instant notification triggered by a physical electric fence around the ship. As shown in a laboratory test and an actual sea test, the three MOB sensing methods developed in this research can perform instant detection and notification actions. We have thus demonstrated a method for the real-time detection of MOB by a shipwrecked ship itself that also promptly proposes a rescue action.
With a new generation of bike sharing services emerging, the development of dockless bike sharing services results in considerable socioeconomic and environmental benefits but also creates new ...issues, such as inappropriate parking behaviors and bike imbalances. To solve the inappropriate parking problem, electric fences have been introduced to guide users to park bikes in designated zones. Considering the role of electric fences in restricting user parking behaviors, an electric fence-based intelligent scheduling method for rebalancing dockless bike sharing systems is proposed in this paper. As a dynamic method that considers the real-time usage of bike sharing systems, an electric fence adjusts its capacity based on real-time information, which guides users to return bikes to electric fences with greater urgency. Because existing approaches require prespecified models and are unable to consider all the intricacies in the dynamic optimization problem, a model-free intelligent scheduling approach based on deep Q-learning that can adapt to the changing distributions of customer arrivals, available bikes, bike locations, and user travel times is used to solve the problem. Finally, a case study involving Beihang University is employed, which shows that the method performs well in rebalancing the bike sharing system and improving the mean utilization (MU) and customer satisfaction (CS).
Conflicts between humans and large carnivores are exacerbated in poor rural areas where people's livelihood depends on livestock ranching. Here we present a pseudo-experimental and co-participatory ...approach to test the effectiveness of a program to mitigate conflicts with jaguars (Panthera onca) in Mexico's Mayan Forest. We worked with eleven ranchers with a recent history of livestock predation by jaguars to codesign, implement, and evaluate changes in their husbandry practices intended to reduce the risk of predation and to increase livestock productivity. We used four parameters to evaluate the effectiveness of the program and found that (1) the use of electric fences and night enclosures greatly reduced the rate of predation on the livestock; (2) the cost of building such protection infrastructure was financially offset by the lack of losses to predation; (3) the application of more science-based husbandry practices led to an overall increase in livestock productivity; and (4) jaguar presence in at least seven of the eleven ranches, showing that the lack of predation was not due to jaguar absence. Our neat results show that conflict between local communities and large carnivores can be largely mitigated through ranchers' capacity building and applying evidence-based husbandry techniques. This approach leads to win-win situations for both jaguars and the local communities and hence can be scaled up to promote coexistence between people and large carnivores in the Mayan Forest and elsewhere.
•Conflicts between humans and large carnivores are exacerbated in poor rural areas.•Protection infrastructure for livestock reduced the rate of predation by jaguars.•Economic cost of livestock protection was offset by lack of predation losses.•Capacity building and evidence-based husbandry techniques can promote coexistence.
•A Markov-chain-based approach for modeling the system states of the EBSS containing e-bike stations and battery cabinet stations.•Integrated battery swapping and rebalancing strategies considering ...both e-bike number and battery power level.•A fast and adaptive one-step Markovian strategy and a globally optimal rolling-horizon Markovian strategy.•Modeling of virtual station for realizing optimized allocation of limited resources.
A new generation of the e-bike sharing system (EBSS) is emerging, where the e-bikes are dockless but need to be parked in designated zones defined by electric fences. The operation of the EBSS relies on the efficient swapping of batteries, in addition to e-bike rebalancing. The replaced power-deficient batteries can be charged in a central depot or street-side cabinets. This paper proposes an approach for modeling the system states of the EBSS containing e-bike stations and battery cabinet stations based on Markov chain dynamics considering both e-bike number and battery power level. Utilizing the prediction of e-bike inventory levels at e-bike stations and batteries’ status at e-bike stations/battery cabinets, a fast and adaptive one-step Markovian strategy is introduced, informing the operating staff of the next station to visit and detailed operations for battery swapping at e-bike/cabinet stations and rebalancing at e-bike stations. Besides, a rolling-horizon Markovian strategy is proposed to make a globally optimal plan of battery swapping and e-bike rebalancing by solving an integer nonlinear programming problem, which gives an approximate upper bound for integrated operations. By considering future demand and making optimal decisions, the proposed Markovian strategies can achieve a profit improvement of over 20% on average, compared to the current strategy used by the industry, as illustrated by the numerical simulations on a real-world EBSS.
Conflicts between humans and mesopredators are frequent and widespread. Over the last decades, conflicts have led to the development and application of different mitigation methods to diminish the ...costs and damage caused by such conflicts. We conducted a systematic literature search and meta‐analysis to assess the influence of different mitigation methods on 3 common nuisance species: raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis). A majority of the studies, from 1963‒2022, were conducted in North America, followed by Australia and Europe. The predation of wildlife species of conservation concern by nuisance species is the main reported source of conflict in the published literature. Lethal control is the most commonly tested method and is generally effective at reducing conflicts based on the calculated effect size. Barriers have mixed effects, with electric fences and nest exclosures both being effective, whereas conventional fences seem to be less effective. Repellents mimicking predators (e.g., guard animal, predator smell) are also effective. Conditioned taste aversion is a promising approach, but no precise product or chemical has proven to be effective. Many interventions suffered from a lack of validation through experimental approach. Research on human–mesopredator conflict mitigation would benefit from repeated studies using the same methods in similar contexts, thus reducing heterogeneity in the results, and by testing new and innovative methods.
Over the last decades, many mitigation methods were developed and applied to diminish the costs and damage caused by human‐mesopredators conflicts. We conducted a systematic literature search and meta‐analysis to assess the influence of different methods on 3 common nuisance species: raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis). We identified which approaches gave the best results, but we also detected limitations in the literature.
Pasture management in Australia's dairy industry requires the manual shifiting of temporary electric fences to maintain pasture quality and growth. Virtual fencing presents an alternative to save ...time and labour costs. We used automated virtual fence (VF) collars to determine the variation in learning of the virtual fence stimuli, and evaluated the success of the technology to contain cows in a predetermined area of pasture. Twelve Holstein-Friesian non-lactating multiparous dairy cows were fitted with the collars, and a VF was used to restrict cows to two grazing allocations (G1 and G2) across six days. Cows received an audio tone (AT) when they approached the virtual fence, and a paired electrical pulse (EP) if they continued forward. The VF contained cows within predetermined areas for 99% of time, but cows spent the least time near the fence (
< 0.01). The number of stimuli reduced through time, demonstrating the ability of cows to learn the VF (
= 0.01). However, the mean number of EP per day ranged from 1 to 6.5 between individuals (
< 0.01). Therefore, successful containment may have a welfare cost for some individuals. Further work should focus on this individual variation, including measures of welfare.
Introduced red foxes (Vulpes vulpes) are a major predator of freshwater turtle nests in Australia. We evaluated the effectiveness of electric fences, in combination with individual nest protection, ...for shielding western saw‐shelled turtle (Myuchelys bellii: Chelidae) nests from predation by foxes. We compared the numbers of raided and intact turtle nests found in paired fenced treatment and unfenced control areas of streambank. We also individually protected all intact nests found in both area types with wire mesh or a steel cage. The total numbers of nests found in treatment and control areas did not significantly differ from parity, but significantly more intact nests were found in treatment areas and significantly more raided nests in control areas. The fences were occasionally damaged by livestock, wildlife and flooding, rendering them inoperative for varying periods of time until repair. However, foxes raided nests inside the fences on only two occasions, despite these breaks in functionality. Our study demonstrates that electric fences can provide an effective method of protecting entire nesting areas from depredation by foxes.
We evaluated the effectiveness of electric fences combined with individual nest protection as a means of protecting the nests of western saw‐shelled turtles from red foxes in Australia. Significantly more intact nests were found in the fenced treatment areas and significantly more raided nests were found in the unfenced control areas. Our study demonstrates that electric fences can provide an effective method of protecting entire nesting areas from depredation by foxes.
Owing to the continuous increase in the damage to farms due to wild animals’ destruction of crops in South Korea, various methods have been proposed to resolve these issues, such as installing ...electric fences and using warning lamps or ultrasonic waves. Recently, new methods have been attempted by applying deep learning-based object-detection techniques to a robot. However, for effective training of a deep learning-based object-detection model, overfitting or biased training should be avoided; furthermore, a huge number of datasets are required. In particular, establishing a training dataset for specific wild animals requires considerable time and labor. Therefore, this study proposes an Extract–Append data augmentation method where specific objects are extracted from a limited number of images via semantic segmentation and corresponding objects are appended to numerous arbitrary background images. Thus, the study aimed to improve the model’s detection performance by generating a rich dataset on wild animals with various background images, particularly images of water deer and wild boar, which are currently causing the most problematic social issues. The comparison between the object detector trained using the proposed Extract–Append technique and that trained using the existing data augmentation techniques showed that the mean Average Precision (mAP) improved by ≥2.2%. Moreover, further improvement in detection performance of the deep learning-based object-detection model can be expected as the proposed technique can solve the issue of the lack of specific data that are difficult to obtain.
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